ITCS 4156

Introduction to Machine Learning

Introduction to the machine learning pipeline of data collection, feature creation, algorithms, and evaluation for classification and regression, with an emphasis on practical applications. Covers fundamental concepts, such as training, validation, overfitting, and error rates in addition to commonly used machine learning algorithms, such as decision trees, Naive Bayes, and random forests.

Units: 3.0